Examples with UnaryCP org.apache.sysml.lops.UnaryCP used on opensource projects

Example 6 with UnaryCP

use of org.apache.sysml.lops.UnaryCP in project incubator-systemml by apache.

the class TernaryOp method constructLopsCovariance.

/**
	 * Method to construct LOPs when op = COVARIANCE.
	 * 
	 * @throws HopsException if HopsException occurs
	 * @throws LopsException if LopsException occurs
	 */
private void constructLopsCovariance() throws HopsException, LopsException {
    if (_op != OpOp3.COVARIANCE)
        throw new HopsException("Unexpected operation: " + _op + ", expecting " + OpOp3.COVARIANCE);
    ExecType et = optFindExecType();
    if (et == ExecType.MR) {
        // combineTertiary -> CoVariance -> CastAsScalar
        CombineTernary combine = CombineTernary.constructCombineLop(CombineTernary.OperationTypes.PreCovWeighted, getInput().get(0).constructLops(), getInput().get(1).constructLops(), getInput().get(2).constructLops(), DataType.MATRIX, getValueType());
        combine.getOutputParameters().setDimensions(getInput().get(0).getDim1(), getInput().get(0).getDim2(), getInput().get(0).getRowsInBlock(), getInput().get(0).getColsInBlock(), getInput().get(0).getNnz());
        CoVariance cov = new CoVariance(combine, DataType.MATRIX, getValueType(), et);
        cov.getOutputParameters().setDimensions(1, 1, 0, 0, -1);
        setLineNumbers(cov);
        UnaryCP unary1 = new UnaryCP(cov, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
        unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(unary1);
        setLops(unary1);
    } else //CP / SPARK
    {
        CoVariance cov = new CoVariance(getInput().get(0).constructLops(), getInput().get(1).constructLops(), getInput().get(2).constructLops(), getDataType(), getValueType(), et);
        cov.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(cov);
        setLops(cov);
    }
}

Example 7 with UnaryCP

use of org.apache.sysml.lops.UnaryCP in project incubator-systemml by apache.

the class QuaternaryOp method constructMRLopsWeightedSquaredLoss.

private void constructMRLopsWeightedSquaredLoss(WeightsType wtype) throws HopsException, LopsException {
    //NOTE: the common case for wsloss are factors U/V with a rank of 10s to 100s; the current runtime only
    //supports single block outer products (U/V rank <= blocksize, i.e., 1000 by default); we enforce this
    //by applying the hop rewrite for Weighted Squared Loss only if this constraint holds. 
    Hop X = getInput().get(0);
    Hop U = getInput().get(1);
    Hop V = getInput().get(2);
    Hop W = getInput().get(3);
    //MR operator selection, part1
    //size U
    double m1Size = OptimizerUtils.estimateSize(U.getDim1(), U.getDim2());
    //size V
    double m2Size = OptimizerUtils.estimateSize(V.getDim1(), V.getDim2());
    boolean isMapWsloss = (!wtype.hasFourInputs() && m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetMap(true));
    if (//broadcast
    !FORCE_REPLICATION && isMapWsloss) {
        //partitioning of U
        boolean needPartU = !U.dimsKnown() || U.getDim1() * U.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lU = U.constructLops();
        if (needPartU) {
            //requires partitioning
            lU = new DataPartition(lU, DataType.MATRIX, ValueType.DOUBLE, (m1Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lU.getOutputParameters().setDimensions(U.getDim1(), U.getDim2(), getRowsInBlock(), getColsInBlock(), U.getNnz());
            setLineNumbers(lU);
        }
        //partitioning of V
        boolean needPartV = !V.dimsKnown() || V.getDim1() * V.getDim2() > DistributedCacheInput.PARTITION_SIZE;
        Lop lV = V.constructLops();
        if (needPartV) {
            //requires partitioning
            lV = new DataPartition(lV, DataType.MATRIX, ValueType.DOUBLE, (m2Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
            lV.getOutputParameters().setDimensions(V.getDim1(), V.getDim2(), getRowsInBlock(), getColsInBlock(), V.getNnz());
            setLineNumbers(lV);
        }
        //map-side wsloss always with broadcast
        Lop wsloss = new WeightedSquaredLoss(X.constructLops(), lU, lV, W.constructLops(), DataType.MATRIX, ValueType.DOUBLE, wtype, ExecType.MR);
        wsloss.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(wsloss);
        Group grp = new Group(wsloss, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grp.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(grp);
        Aggregate agg1 = new Aggregate(grp, HopsAgg2Lops.get(AggOp.SUM), DataType.MATRIX, ValueType.DOUBLE, ExecType.MR);
        // aggregation uses kahanSum 
        agg1.setupCorrectionLocation(CorrectionLocationType.NONE);
        agg1.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(agg1);
        UnaryCP unary1 = new UnaryCP(agg1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
        unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(unary1);
        setLops(unary1);
    } else //general case
    {
        //MR operator selection part 2
        boolean cacheU = !FORCE_REPLICATION && (m1Size < OptimizerUtils.getRemoteMemBudgetReduce());
        boolean cacheV = !FORCE_REPLICATION && ((!cacheU && m2Size < OptimizerUtils.getRemoteMemBudgetReduce()) || (cacheU && m1Size + m2Size < OptimizerUtils.getRemoteMemBudgetReduce()));
        Group grpX = new Group(X.constructLops(), Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grpX.getOutputParameters().setDimensions(X.getDim1(), X.getDim2(), X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(grpX);
        Lop grpW = W.constructLops();
        if (grpW.getDataType() == DataType.MATRIX) {
            grpW = new Group(W.constructLops(), Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
            grpW.getOutputParameters().setDimensions(W.getDim1(), W.getDim2(), W.getRowsInBlock(), W.getColsInBlock(), -1);
            setLineNumbers(grpW);
        }
        Lop lU = null;
        if (cacheU) {
            //partitioning of U for read through distributed cache
            boolean needPartU = !U.dimsKnown() || U.getDim1() * U.getDim2() > DistributedCacheInput.PARTITION_SIZE;
            lU = U.constructLops();
            if (needPartU) {
                //requires partitioning
                lU = new DataPartition(lU, DataType.MATRIX, ValueType.DOUBLE, (m1Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
                lU.getOutputParameters().setDimensions(U.getDim1(), U.getDim2(), getRowsInBlock(), getColsInBlock(), U.getNnz());
                setLineNumbers(lU);
            }
        } else {
            //replication of U for shuffle to target block
            //ncol of t(V) -> nrow of V determines num replicates
            Lop offset = createOffsetLop(V, false);
            lU = new RepMat(U.constructLops(), offset, true, V.getDataType(), V.getValueType());
            lU.getOutputParameters().setDimensions(U.getDim1(), U.getDim2(), U.getRowsInBlock(), U.getColsInBlock(), U.getNnz());
            setLineNumbers(lU);
            Group grpU = new Group(lU, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
            grpU.getOutputParameters().setDimensions(U.getDim1(), U.getDim2(), U.getRowsInBlock(), U.getColsInBlock(), -1);
            setLineNumbers(grpU);
            lU = grpU;
        }
        Lop lV = null;
        if (cacheV) {
            //partitioning of V for read through distributed cache
            boolean needPartV = !V.dimsKnown() || V.getDim1() * V.getDim2() > DistributedCacheInput.PARTITION_SIZE;
            lV = V.constructLops();
            if (needPartV) {
                //requires partitioning
                lV = new DataPartition(lV, DataType.MATRIX, ValueType.DOUBLE, (m2Size > OptimizerUtils.getLocalMemBudget()) ? ExecType.MR : ExecType.CP, PDataPartitionFormat.ROW_BLOCK_WISE_N);
                lV.getOutputParameters().setDimensions(V.getDim1(), V.getDim2(), getRowsInBlock(), getColsInBlock(), V.getNnz());
                setLineNumbers(lV);
            }
        } else {
            //replication of t(V) for shuffle to target block
            Transform ltV = new Transform(V.constructLops(), HopsTransf2Lops.get(ReOrgOp.TRANSPOSE), getDataType(), getValueType(), ExecType.MR);
            ltV.getOutputParameters().setDimensions(V.getDim2(), V.getDim1(), V.getColsInBlock(), V.getRowsInBlock(), V.getNnz());
            setLineNumbers(ltV);
            //nrow of U determines num replicates
            Lop offset = createOffsetLop(U, false);
            lV = new RepMat(ltV, offset, false, V.getDataType(), V.getValueType());
            lV.getOutputParameters().setDimensions(V.getDim2(), V.getDim1(), V.getColsInBlock(), V.getRowsInBlock(), V.getNnz());
            setLineNumbers(lV);
            Group grpV = new Group(lV, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
            grpV.getOutputParameters().setDimensions(V.getDim2(), V.getDim1(), V.getColsInBlock(), V.getRowsInBlock(), -1);
            setLineNumbers(grpV);
            lV = grpV;
        }
        //reduce-side wsloss w/ or without broadcast
        Lop wsloss = new WeightedSquaredLossR(grpX, lU, lV, grpW, DataType.MATRIX, ValueType.DOUBLE, wtype, cacheU, cacheV, ExecType.MR);
        wsloss.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(wsloss);
        Group grp = new Group(wsloss, Group.OperationTypes.Sort, DataType.MATRIX, ValueType.DOUBLE);
        grp.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(grp);
        Aggregate agg1 = new Aggregate(grp, HopsAgg2Lops.get(AggOp.SUM), DataType.MATRIX, ValueType.DOUBLE, ExecType.MR);
        // aggregation uses kahanSum 
        agg1.setupCorrectionLocation(CorrectionLocationType.NONE);
        agg1.getOutputParameters().setDimensions(1, 1, X.getRowsInBlock(), X.getColsInBlock(), -1);
        setLineNumbers(agg1);
        UnaryCP unary1 = new UnaryCP(agg1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
        unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(unary1);
        setLops(unary1);
    }
}

Example 8 with UnaryCP

use of org.apache.sysml.lops.UnaryCP in project incubator-systemml by apache.

the class UnaryOp method constructLopsIQM.

private Lop constructLopsIQM() throws HopsException, LopsException {
    ExecType et = optFindExecType();
    Hop input = getInput().get(0);
    if (et == ExecType.MR) {
        CombineUnary combine = CombineUnary.constructCombineLop(input.constructLops(), DataType.MATRIX, getValueType());
        combine.getOutputParameters().setDimensions(input.getDim1(), input.getDim2(), input.getRowsInBlock(), input.getColsInBlock(), input.getNnz());
        SortKeys sort = SortKeys.constructSortByValueLop(combine, SortKeys.OperationTypes.WithoutWeights, DataType.MATRIX, ValueType.DOUBLE, ExecType.MR);
        // Sort dimensions are same as the first input
        sort.getOutputParameters().setDimensions(input.getDim1(), input.getDim2(), input.getRowsInBlock(), input.getColsInBlock(), input.getNnz());
        Data lit = Data.createLiteralLop(ValueType.DOUBLE, Double.toString(0.25));
        lit.setAllPositions(this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
        PickByCount pick = new PickByCount(sort, lit, DataType.MATRIX, getValueType(), PickByCount.OperationTypes.RANGEPICK);
        pick.getOutputParameters().setDimensions(-1, -1, getRowsInBlock(), getColsInBlock(), -1);
        setLineNumbers(pick);
        PartialAggregate pagg = new PartialAggregate(pick, HopsAgg2Lops.get(Hop.AggOp.SUM), HopsDirection2Lops.get(Hop.Direction.RowCol), DataType.MATRIX, getValueType());
        setLineNumbers(pagg);
        // Set the dimensions of PartialAggregate LOP based on the
        // direction in which aggregation is performed
        pagg.setDimensionsBasedOnDirection(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock());
        Group group1 = new Group(pagg, Group.OperationTypes.Sort, DataType.MATRIX, getValueType());
        group1.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
        setLineNumbers(group1);
        Aggregate agg1 = new Aggregate(group1, HopsAgg2Lops.get(Hop.AggOp.SUM), DataType.MATRIX, getValueType(), ExecType.MR);
        agg1.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
        agg1.setupCorrectionLocation(pagg.getCorrectionLocation());
        setLineNumbers(agg1);
        UnaryCP unary1 = new UnaryCP(agg1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
        unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(unary1);
        Unary iqm = new Unary(sort, unary1, Unary.OperationTypes.MR_IQM, DataType.SCALAR, ValueType.DOUBLE, ExecType.CP);
        iqm.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
        setLineNumbers(iqm);
        return iqm;
    } else {
        SortKeys sort = SortKeys.constructSortByValueLop(input.constructLops(), SortKeys.OperationTypes.WithoutWeights, DataType.MATRIX, ValueType.DOUBLE, et);
        sort.getOutputParameters().setDimensions(input.getDim1(), input.getDim2(), input.getRowsInBlock(), input.getColsInBlock(), input.getNnz());
        PickByCount pick = new PickByCount(sort, null, getDataType(), getValueType(), PickByCount.OperationTypes.IQM, et, true);
        pick.getOutputParameters().setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
        setLineNumbers(pick);
        return pick;
    }
}

Example 9 with UnaryCP

use of org.apache.sysml.lops.UnaryCP in project incubator-systemml by apache.

the class Hop method createOffsetLop.

public static Lop createOffsetLop(Hop hop, boolean repCols) throws HopsException, LopsException {
    Lop offset = null;
    if (ConfigurationManager.isDynamicRecompilation() && hop.dimsKnown()) {
        // If dynamic recompilation is enabled and dims are known, we can replace the ncol with 
        // a literal in order to increase the piggybacking potential. This is safe because append 
        // is always marked for recompilation and hence, we have propagated the exact dimensions.
        offset = Data.createLiteralLop(ValueType.INT, String.valueOf(repCols ? hop.getDim2() : hop.getDim1()));
    } else {
        offset = new UnaryCP(hop.constructLops(), repCols ? UnaryCP.OperationTypes.NCOL : UnaryCP.OperationTypes.NROW, DataType.SCALAR, ValueType.INT);
    }
    offset.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
    offset.setAllPositions(hop.getBeginLine(), hop.getBeginColumn(), hop.getEndLine(), hop.getEndColumn());
    return offset;
}

Example 10 with UnaryCP

use of org.apache.sysml.lops.UnaryCP in project incubator-systemml by apache.

the class LeftIndexingOp method constructLops.

@Override
public Lop constructLops() throws HopsException, LopsException {
    //return already created lops
    if (getLops() != null)
        return getLops();
    try {
        ExecType et = optFindExecType();
        if (et == ExecType.MR) {
            //the right matrix is reindexed
            Lop top = getInput().get(2).constructLops();
            Lop bottom = getInput().get(3).constructLops();
            Lop left = getInput().get(4).constructLops();
            Lop right = getInput().get(5).constructLops();
            //right hand matrix
            Lop nrow = new UnaryCP(getInput().get(0).constructLops(), OperationTypes.NROW, DataType.SCALAR, ValueType.INT);
            Lop ncol = new UnaryCP(getInput().get(0).constructLops(), OperationTypes.NCOL, DataType.SCALAR, ValueType.INT);
            Lop rightInput = null;
            if (isRightHandSideScalar()) {
                //insert cast to matrix if necessary (for reuse MR runtime)
                rightInput = new UnaryCP(getInput().get(1).constructLops(), OperationTypes.CAST_AS_MATRIX, DataType.MATRIX, ValueType.DOUBLE);
                rightInput.getOutputParameters().setDimensions((long) 1, (long) 1, (long) ConfigurationManager.getBlocksize(), (long) ConfigurationManager.getBlocksize(), (long) -1);
            } else
                rightInput = getInput().get(1).constructLops();
            RangeBasedReIndex reindex = new RangeBasedReIndex(rightInput, top, bottom, left, right, nrow, ncol, getDataType(), getValueType(), et, true);
            reindex.getOutputParameters().setDimensions(getInput().get(0).getDim1(), getInput().get(0).getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
            setLineNumbers(reindex);
            Group group1 = new Group(reindex, Group.OperationTypes.Sort, DataType.MATRIX, getValueType());
            group1.getOutputParameters().setDimensions(getInput().get(0).getDim1(), getInput().get(0).getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
            setLineNumbers(group1);
            //the left matrix is zeroed out
            ZeroOut zeroout = new ZeroOut(getInput().get(0).constructLops(), top, bottom, left, right, getInput().get(0).getDim1(), getInput().get(0).getDim2(), getDataType(), getValueType(), et);
            zeroout.getOutputParameters().setDimensions(getInput().get(0).getDim1(), getInput().get(0).getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
            setLineNumbers(zeroout);
            Group group2 = new Group(zeroout, Group.OperationTypes.Sort, DataType.MATRIX, getValueType());
            group2.getOutputParameters().setDimensions(getInput().get(0).getDim1(), getInput().get(0).getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
            setLineNumbers(group2);
            Binary binary = new Binary(group1, group2, HopsOpOp2LopsB.get(Hop.OpOp2.PLUS), getDataType(), getValueType(), et);
            binary.getOutputParameters().setDimensions(getInput().get(0).getDim1(), getInput().get(0).getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
            setLineNumbers(binary);
            setLops(binary);
        } else if (et == ExecType.SPARK) {
            Hop left = getInput().get(0);
            Hop right = getInput().get(1);
            LeftIndexingMethod method = getOptMethodLeftIndexingMethod(left.getDim1(), left.getDim2(), left.getRowsInBlock(), left.getColsInBlock(), left.getNnz(), right.getDim1(), right.getDim2(), right.getNnz(), right.getDataType());
            //insert cast to matrix if necessary (for reuse broadcast runtime)
            Lop rightInput = right.constructLops();
            if (isRightHandSideScalar()) {
                rightInput = new UnaryCP(rightInput, (left.getDataType() == DataType.MATRIX ? OperationTypes.CAST_AS_MATRIX : OperationTypes.CAST_AS_FRAME), left.getDataType(), right.getValueType());
                long bsize = ConfigurationManager.getBlocksize();
                rightInput.getOutputParameters().setDimensions(1, 1, bsize, bsize, -1);
            }
            LeftIndex leftIndexLop = new LeftIndex(left.constructLops(), rightInput, getInput().get(2).constructLops(), getInput().get(3).constructLops(), getInput().get(4).constructLops(), getInput().get(5).constructLops(), getDataType(), getValueType(), et, getSpLixCacheType(method));
            setOutputDimensions(leftIndexLop);
            setLineNumbers(leftIndexLop);
            setLops(leftIndexLop);
        } else {
            LeftIndex left = new LeftIndex(getInput().get(0).constructLops(), getInput().get(1).constructLops(), getInput().get(2).constructLops(), getInput().get(3).constructLops(), getInput().get(4).constructLops(), getInput().get(5).constructLops(), getDataType(), getValueType(), et);
            setOutputDimensions(left);
            setLineNumbers(left);
            setLops(left);
        }
    } catch (Exception e) {
        throw new HopsException(this.printErrorLocation() + "In LeftIndexingOp Hop, error in constructing Lops ", e);
    }
    //add reblock/checkpoint lops if necessary
    constructAndSetLopsDataFlowProperties();
    return getLops();
}